1,720,959 research outputs found
Conditional inference for binary panel data models with predetermined covariates
No full textA fixed-effects logit model that accounts for feedback effects of the dependent variable on the covariates is proposed. The model is formulated by including leads of the predetermined covariates among the regressors and it is proved to satisfy certain theoretical properties under some regularity conditions on the distribution of the covariates. Estimation is based on the Conditional Maximum Likelihood (CML) method for the static logit model and the Pseudo-CML (PCML) method for the corresponding dynamic formulation. Both methods have good finite-sample properties even when the required regularity conditions are not satisfied. An application is provided about female labor supply where we jointly account for the predetermined number of children and husbands’ income. Differently from previous studies, it emerges that female employment history does not affect future fertility choices and the husband's earnings, as no evidence of feedback effects is found
Firing Costs and Job Loss: The Case of the Italian Jobs Act
Full text linkA recent reform in the Italian labour market has modified the permanent contract by reducing firing costs. Using a discontinuity in the application of the reform, we evaluate its effect on the probability of being still employed about three and a half years later. In contrast with theoretical predictions, we find that the job survival probability is not smaller for the treated and even significantly larger in some cases. We investigate the composition of permanent workers hired after the reform and we find evidence of treated firms changing their recruitment strategy in favour of potentially more productive workers
Testing for state dependence in the fixed-effects ordered logit model
Full text linkWe propose a test for state dependence in the fixed-effects ordered logit, based on the Quadratic Exponential model. The test can be applied to models where persistence lies either in the latent or observed response variable
A Finite Mixture Latent Trajectory Model for Hirings and Separations in the Labor Market
No full textConditional inference and bias reduction for partial effects estimation of fixed-effects logit models
Full text linkWe propose a multiple-step procedure to compute average partial effects (APEs) for fixed-effects static and dynamic logit models estimated by (pseudo) conditional maximum likelihood. As individual effects are eliminated by conditioning on suitable sufficient statistics, we propose evaluating the APEs at the maximum likelihood estimates for the unobserved heterogeneity, along with the fixed-T consistent estimator of the slope parameters, and then reducing the induced bias in the APEs by an analytical correction. The proposed estimator has bias of order O(T-2), it performs well in finite samples and, when the dynamic logit model is considered, better than alternative plug-in strategies based on bias-corrected estimates for the slopes, especially in panels with short T. We provide a real data application based on labour supply of married women
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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